A Tumor-Agnostic, Topology-Informed Scoring Framework for Drug Repurposing: Application to CDK4/6 Inhibitor Resistance in HR+ Breast Cancer

Background: Therapeutic resistance to CDK4/6 inhibitors (CDK4/6i) remains a critical barrier in HR+ breast cancer. While network-based approaches offer a route to identify salvage therapies, existing methods often rely on inconsistent centrality metrics or retrospective public transcriptomes, lacking a unified framework to translate topology into pharmacological actionability. Methods: We developed the Topology-Integrated Hubness Score (TIHS), a quantitative framework that integrates five orthogonal network metrics into a unified hubness vector. To rigorously validate this framework and overcome the limitations of public bulk datasets, we combined cross-cohort statistical benchmarking with original RNA-sequencing data generated from a laboratory-derived palbociclib-resistant model (MCF7-PR). TIHS was applied to prioritize repurposing candidates by overlaying network hubness with drug–target affinity profiles. Results: Methodologically, TIHS demonstrated robust cross-dataset stability (cosine similarity ≥ 0.98) and statistically outperformed single-metric approaches in predicting drug sensitivity. In application, the framework identified sorafenib as a top-ranked candidate for reversing CDK4/6i resistance. Experimental validation confirmed these predictions: sorafenib significantly resensitized resistant cells (IC50 reduction from 6.57 μM to 1.15 μM), and molecular dynamics simulations supported stable binding to the TIHS-prioritized hub, FGFR3. Furthermore, functional assays involving siRNA-mediated knockdown validated that FGFR3 is mechanistically required for the sorafenib resensitization phenotype. Conclusions: This study presents TIHS as a mechanism-agnostic, experimentally validated bridge between resistance-state transcriptomes and clinical decision-making. By coupling computational prioritization with in vitro functional verification, we demonstrate that targeting topology-defined hubs is a viable strategy for overcoming therapy resistance.